Agus Salim
Papers
1
Total Citations
2
H-Index
1
About
Agus Salim is a researcher specializing in robotics and control systems, with a particular focus on mobile robot navigation and material handling automation. His work centers on improving locomotion processes in autonomous robots through advanced control methodologies. Salim’s key contribution involves the implementation of hybrid control systems, most notably integrating Artificial Neural Networks (ANN) with traditional PID controllers to enhance the walking and movement processes of material handling robot prototypes. This approach addresses inherent limitations in conventional PID control, particularly the challenging task of manually tuning parameters such as Kp, Ki, and Kd for optimal performance. By combining ANN’s adaptive learning capabilities with PID’s stability, his research offers a more robust and efficient solution for real-time robot control. While his most-cited paper, "IMPLEMENTASI METODE HYBRID ARTIFICIAL NEURAL NETWORK (ANN) – PID UNTUK PERBAIKAN PROSES BERJALAN PADA PROTOTYPE ROBOT MATERIAL HANDLING" (2014), has garnered 2 citations, it represents foundational work in hybrid control strategies for robotics. Salim’s research contributes to the broader field of intelligent automation, offering practical improvements for industrial robots requiring precise and adaptive movement control.
Research Focus
Key Achievements
Top Papers
- 1